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Publication numberUS5903641 A
Publication typeGrant
Application numberUS 08/790,010
Publication dateMay 11, 1999
Filing dateJan 28, 1997
Priority dateJan 28, 1997
Fee statusPaid
Also published asCA2226093A1, CA2226093C, DE69701350D1, EP0855826A2, EP0855826A3, EP0855826B1
Publication number08790010, 790010, US 5903641 A, US 5903641A, US-A-5903641, US5903641 A, US5903641A
InventorsAlan V. Tonisson
Original AssigneeLucent Technologies Inc.
Export CitationBiBTeX, EndNote, RefMan
External Links: USPTO, USPTO Assignment, Espacenet
Automatic dynamic changing of agents' call-handling assignments
US 5903641 A
Abstract
An agent vector monitors selected performance parameters of a call center, such as service times, in-queue times, call volumes, call abandonment rates, benefits derived from having different agents handle calls requiring different skills, proportions of work spent by agents on handling calls requiring different skills, etc., and automatically adjusts agents' call-handling assignments, for example, by changing the skills to which an agent is assigned or by changing the relative priorities of the agent's skills, in order to optimize a predefined objective. The objective is a selected performance characteristic of the call center, for example, the total benefit to the call center of individual ones of the agents handling calls requiring individual agent skills.
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Claims(25)
The invention claimed is:
1. An arrangement for automatically assigning call center agents to skills in a call center wherein individual calls requiring different skills are handled by a plurality of agents who are individually assigned to different ones of the skills, comprising:
means for automatically determining present values of call center parameters that impact a predetermined performance characteristic of the call center, which characteristic is sought to be optimized, the parameters including a parameter indicating actual assignments of the plurality of call center agents to work handling calls requiring individual ones of the skills;
means for automatically performing an optimization function, using the determined present values, on the predetermined performance characteristic to determine optimum assignments of the plurality of call center agents to skills that optimize the predetermined performance characteristic; and
means for automatically adjusting the actual assignments of the plurality of call center agents to skills, to bring the actual assignments closer to the determined optimum assignments.
2. The arrangement of claim 1 wherein:
the predetermined performance characteristic comprises a total benefit to the call center of individual ones of the agents handling calls requiring individual ones of the skills.
3. The arrangement of claim 1 wherein:
the parameter of the actual assignments of the plurality of call center agents to skills includes a parameter (Rs,a) of proportions of work that individual ones of the agents (a) spend handling calls requiring individual ones of the skills (s).
4. The arrangement of claim 3 wherein:
the predetermined performance characteristic comprises a total benefit (B) to the call center of the individual ones of the agents (a) handling calls requiring the individual ones of the skills (s).
5. The arrangement of claim 4 wherein:
the call center parameters further include
for each agent (a) and each skill (s), a benefit (Ls,a) to the call center of aid each agent (a) handling calls requiring said each skill (s) per unit of time,
for each skill (s), a volume (As) of abandoned calls requiring said each skill (s), and
for each skill (s), a penalty (Ps) for each abandoned call requiring said each skill (s).
6. The arrangement of claim 5 wherein performing the optimization function comprises
maximizing ##EQU9##
7. The arrangement of claim 5 wherein: the call center parameters further include
for each agent (a) and each skill (s), a capacity (Cs,a) of said each agent (a) to handle calls requiring said each skill (s), and
for each skill (s), a volume (Vs) of arriving calls requiring said each skill (s); and
performing the optimization function comprises
maximizing ##EQU10##
8. The arrangement of claim 5 wherein: the call center parameters further include
for each skill (s), a weight (Ws) associated with said each skill (s); and
performing the optimization function comprises
maximizing ##EQU11##
9. The arrangement of claim 4 wherein: the call center parameters further include
for each agent (a) and each skill (s), a benefit (Bs,a) to the call center of said each agent (a) handling a call requiring said each skill (s),
for each agent (a) and each skill (s), a capacity (Cs,a) of said each agent (a) to handle calls requiring said each skill (s),
for each skill (s), a volume (As) of abandoned calls requiring said each skill (s), and
for each skill (s), a penalty (Ps) for each abandoned call requiring said each skill (s).
10. The arrangement of claim 9 wherein:
performing the optimization function comprises
maximizing ##EQU12##
11. The arrangement of claim 4 wherein: the call center parameters further include
for each agent (a) and each skill (s), a benefit (Bs,a) to the call center of said each agent (a) handling a call requiring said each skill (s),
for each agent (a) and each skill (s), a volume (Vs,a) of calls requiring said each skill (s) handled by said each agent (a),
for each skill (s), a volume (As) of abandoned calls requiring said each skill (s), and
for each skill (s), a penalty (Ps) for each abandoned call requiring said each skill (s).
12. The arrangement of claim 11 wherein:
performing the optimization function comprises
maximizing ##EQU13##
13. The arrangement of claim 4 wherein: the call center parameters further include
for each agent (a) and each skill (s), a benefit (Bs,a) to the call center of said each agent (a) handling a call requiring said each skill (s),
for each agent (s) and each skill (s), a capacity (Cs,a) of said each agent (a) to handle calls requiring said each skill (s),
for each skill (s), a volume (As) of abandoned calls requiring said each skill (s), and
for each skill (s), a penalty (Ps) for each abandoned call requiring said each skill (s).
14. The arrangement of claim 13 wherein:
performing the optimization function comprises
maximizing ##EQU14##
15. The arrangement of claim 4 wherein: the call center parameters further include
for each agent (a) and each skill (s), a benefit (Bs,a) to the call center of said each agent (a) handling a call requiring said each skill (s),
for each skill (s), a volume (Vs) of arriving calls requiring said each skill (s),
for each skill (s), a volume (As) of abandoned calls requiring said each skill (s), and
for each skill (s), a penalty (Ps) for each abandoned call requiring said each skill (s).
16. The arrangement of claim 15 wherein:
performing the optimization function comprises
maximizing ##EQU15##
17. The arrangement of claim 1 wherein: the parameter of the actual assignments of the plurality of call center agents to skills includes a parameter of actual proportions of work that individual ones of the agents spend handling calls requiring individual ones of the skills;
the optimum assignments of the plurality of call center agents to skills include optimum proportions of work for individual ones of the agents to spend handling calls requiring the individual ones of the skills; and
the adjusting means comprise
means for assigning an individual agent to handle calls requiring an individual skill in response to the optimum proportion of work for the individual agent to spend handling calls requiring the individual skill exceeding the actual proportion of work that the individual agent spent handling calls requiring the individual skill and the individual agent not being assigned to handle calls requiring the individual skill, and for freeing the individual agent from handling calls requiring the individual skill in response to the actual proportion of work that the individual agent spent handling calls requiring the individual skill exceeding the optimum proportion of work for the individual agent to spend handling calls requiring the individual skill and the individual agent being assigned to handle calls requiring the individual skill.
18. A method of automatically assigning call center agents to skills in a call center wherein individual calls requiring different skills are handled by a plurality of agents who are individually assigned to different ones of the skills, comprising the steps of:
automatically determining present values of call center parameters that impact a predetermined performance characteristic of the call center, which characteristic is sought to be optimized, the parameters including a parameter indicating actual assignments of the plurality of call center agents to work handling calls requiring individual ones of the skills;
automatically performing an optimization function, using the determined present values, on the predetermined performance characteristic to determine optimum assignments of the plurality of call center agents to skills that optimize the predetermined performance characteristic; and
automatically adjusting the actual assignments of the plurality of call center agents to skills, to bring the actual assignments closer to the determined optimum assignments.
19. The method of claim 18 wherein:
the predetermined performance characteristic comprises a total benefit to the call center of individual ones of the agents handling calls requiring individual ones of the skills.
20. The method of claim 18 wherein:
the parameter of the actual assignments of the plurality of call center agents to skills includes a parameter of proportions of work that individual ones of the agents spend handling calls requiring individual ones of the skills;
the step of performing comprises the step of
automatically determining optimum proportions of work for individual ones of the agents to spend handling calls requiring individual ones of the skills; and
the step of adjusting comprises the step of
bringing the actual proportions closer to the optimum proportions.
21. The method of claim 20 wherein:
the step of bringing comprises the steps of
assigning an individual agent to handle calls requiring an individual skill in response to the optimum proportion for the individual agent exceeding the actual proportion for the individual agent and the individual agent not being assigned to handle calls requiring the individual skill, and
freeing the individual agent from handling calls requiring the individual skill in response to the actual proportion for the individual agent exceeding the optimum proportion for the individual agent and the individual agent being assigned to handle calls requiring the individual skill.
22. A computer-usable program storage device having embodied therein means for automatically assigning call center agents to skills in a call center, wherein individual calls requiring different skills are handled by a plurality of agents who are individually assigned to different ones of the skills, said means being computer-readable program code means for causing the computer to perform the functions of:
determining present values of call center parameters that impact a predetermined performance characteristic of the call center, which characteristic is sought to be optimized, the parameters including a parameter indicating actual assignments of the plurality of call center agents to work handling calls requiring individual ones of the skills;
performing an optimization function, using the determined present values, on the predetermined performance characteristic to determine optimum assignments of the plurality of call center agents to skills that optimize the predetermined performance characteristic; and
adjusting the actual assignments of the plurality of call center is agents to skills, to bring the actual assignments closer to the determined optimum assignments.
23. The device of claim 22 wherein:
the predetermined performance characteristic comprises a total benefit to the call center of individual ones of the agents handling calls requiring individual ones of the skills.
24. The device of claim 22 wherein:
the parameter of the actual assignments of the plurality of call center agents to skills includes a parameter of proportions of work that individual ones of the agents spend handling calls requiring individual ones of the skills;
the step of performing comprises the step of
determining optimum proportions of work for individual ones of the agents to spend handling calls requiring individual ones of the skills; and
the step of adjusting comprises the step of
bringing the actual proportions closer to the optimum proportions.
25. The device of claim 24 wherein:
the step of bringing comprises the steps of
assigning an individual agent to handle calls requiring an individual skill, in response to the optimum proportion for the individual agent exceeding the actual proportion for the individual agent and the individual agent not being assigned to handle calls requiring the individual skill; and
freeing the individual agent from handling calls requiring the individual skill, in response to the actual proportion for the individual agent exceeding the optimum proportion for the individual agent and the individual agent being assigned to handle calls requiring the individual skill.
Description
TECHNICAL FIELD

This invention relates to automatic call distribution (ACD) systems, also variously referred to as call centers or telemarketing systems.

BACKGROUND OF THE INVENTION

ACD systems distribute calls incoming to a call center for handling to any suitable ones of available call-handling agents according to some predefined criteria. In advanced modern-day ACD systems, suitability of an agent to handle a call is determined by matching skills that are needed to handle a particular call against the skills possessed by the agents who are available to handle that call. An illustrative such system is disclosed in U.S. Pat. No. 5,206,903.

It often happens that the call center becomes overloaded by calls, so that no suitable agents are available to handle the calls at the moment that the calls come in. The calls then back up, and are placed in call queues based upon some predefined criteria, such as the skills that are needed to handle them. There they await suitable agents becoming free and available to handle them. When the ACD system detects that an agent has become available to handle a call, the ACD system delivers to the agent the highest-priority oldest-waiting call that matches the agent's highest skill. Generally the only condition that results in a call not being delivered to an available agent is that there are no calls waiting to be handled that require any of the available agent's skills. The available agents are then placed in agent queues based upon some predefined criteria, such as the skills which they possess. There they await the arrival of suitable calls for handling. When a call arrives, the ACD system delivers the call to the longest-waiting agent whose skills best match the call's requirements. Call center efficiency typically requires that both calls and agents spend as little time in queues as possible.

As call volumes of calls requiring different skills change, agents may need to be reassigned to different skills (i.e., to handling calls requiring different ones of the skills possessed by the agents) to balance the call load. The task of monitoring service levels, determining which skills each agent should be logged into at any given time, and moving the agents between skills to maintain optimal staffing is complex, time-consuming, laborious, and slow. This function is normally carried out manually by the call center supervisor. Consequently, the supervisor must almost constantly monitor the performance of the call center and adjust agent assignments as call volumes change. Even then, the supervisor's reactions to changes in the call center's workload are often either delayed if properly computed or inaccurate if done reflexively, based only on experience and without computation, to avoid delay. Moreover, the call center supervisors are normally the most experienced employees and the call center's most valuable resource, whose time could be better spent on other call center work.

SUMMARY OF THE INVENTION

This invention is directed to solving these and other problems and disadvantages of the prior art. Generally according to the invention, there is provided an arrangement that monitors a call center's performance parameters--such as service times, in-queue times, call volumes, call abandonment rates, benefits derived from having different agents handle calls requiring different skills, proportions of work (e.g., time or calls handled) spent by agents on handling calls requiring different skills, etc.--and automatically adjusts agents' call-handling assignments--for example, by changing the skills to which an agent is assigned (logged into) or by changing the relative priorities (levels of expertise) of the agent's skills--in order to optimize a predefined objective or objectives. The objective is a selected performance characteristic of the call center, such as the total benefit to the call center of individual ones of the agents handling calls requiring individual agent skills. The term "automatically" is used herein to mean by means of a machine (e.g., an ACD or some other processing system or computer), as opposed to manually by the call-center supervisor or some other person.

Specifically according to the invention, call center agents are automatically assigned to skills in a call center wherein individual calls requiring different skills are handled by a plurality of agents who are individually assigned to different ones of the skills, in the following manner. The present values of call center parameters that impact a predetermined performance characteristic of the call center are automatically determined. The characteristic is one which is sought to be optimized--for example, the total benefit to the call center of individual ones of the agents handling calls requiring individual ones of the skills. The parameters include actual assignments of the plurality of call center agents to skills. The parameter of actual assignments of the plurality of call center agents to skills preferably is the parameter of actual proportions of work that individual ones of the agents spend handling calls requiring individual ones of the skills. Then an optimization function that uses the determined parameter values is automatically performed on the predetermined performance characteristic to determine optimum assignments of the plurality of call center agents to skills that optimize the predetermined performance characteristic. The optimum assignments of the plurality of call center agents to skills preferably are optimum proportions of work for individual ones of the agents to spend handling calls requiring the individual ones of the skills. The actual assignments of the plurality of call center to skills are then automatically adjusted to bring the actual assignments closer to the determined optimum assignments. Preferably, the adjusting involves assigning an individual agent to handle calls requiring an individual skill, in response to the optimum proportion of work for the individual agent to spend handling calls requiring the individual skill exceeding the actual proportion of work that the individual agent spent handling calls requiring the individual skill and the individual agent not being assigned to handle calls requiring the individual skill, and further preferably involves freeing ("un-assigning") the individual agent from handling calls requiring the individual skill, in response to the actual proportion of work that the individual agent spent handling calls requiring the individual skill exceeding the optimum proportion of work for the individual agent to spend handling calls requiring the individual skill and the individual agent being assigned to handle calls requiring the individual skill.

The invention advantageously frees call center supervisors from having to decide which agents to assign to which skills as call volumes change. It provides more efficient allocation of call center resources (agents) than could be reasonably achieved by manual means. It allows the call center supervisor to manage a call center simply by deciding which performance characteristic should be optimized. The operation of the call center is then automatically adjusted to optimize the selected performance characteristic. It automates many aspects of running the call center, thereby freeing the call center supervisor to do other things, while still retaining a high degree of control for the supervisor. And it reduces the need to write complicated call vectors or individual per-agent agent vectors to control the distribution of calls.

Furthermore, the invention is very flexible and can be used to control many aspects of a call center. For example, it can be used to extract information from the optimization function for use by features like "wizards" which advise a supervisor on the best course of action to take, e.g., "Add 3 more agents skilled in Sales". This can form the basis of an expert system for call center applications. The optimization function can also be used in conjunction with predicted call volumes to allow optimum agent allocations to be calculated ahead of time and to advise a call center supervisor on when to add agents with particular skills. This facility can be used to assist in scheduling of agents.

These and other advantages and features of the invention will become more apparent from the following description of an illustrative embodiment of the invention taken together with the drawing.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a block diagram of a call center that includes an illustrative embodiment of the invention; and

FIGS. 2-4 are flow diagrams of operations performed by an agent vector of the call center of FIG. 1 upon agent log in, agent log off, and periodically to optimize the operation of the call center of FIG. 1, respectively.

DETAILED DESCRIPTION

1. Call Center General Description

FIG. 1 shows an illustrative call center. As is conventional, the call center comprises a plurality of telephone lines and/or trunks 100 selectively interconnected with a plurality of agent positions 102-104 via an ACD system 101. Each agent position 102-104 includes a voice-and-data terminal 105 for use by a corresponding agent 106-108 in handling calls. Terminals 105 are connected to ACD system 101 by a voice-and-data transmission medium 109. Also, included in ACD system 101 is a conventional basic call management system (BCMS) and connected to ACD system 101 is a conventional call management system (CMS) that gather call records and call-center statistics for use in managing the call center and in generating call-center reports. CMS and BCMS will hereafter be referred to jointly as CMS 110.

ACD system 101 is illustratively the Lucent Technologies DefinityŽ private-branch exchange (PBX)-based ACD system. It is a stored-program-controlled system that conventionally includes interfaces to external communications links, a communications switching fabric, service circuits (e.g., tone generators, announcement circuits, etc.), memory for storing control programs and data, and a processor for executing the stored control programs to control the interfaces and the fabric and to provide automatic call-distribution functionality. Included among the data stored in a memory of ACD system 101 are a set of call queues 120 and a set of agent queues 130. Each call queue 121-129 corresponds to a different agent skill, as does each agent queue 131-139. Conventionally, calls are prioritized, and either are enqueued in individual ones of call queues 120 in their order of priority or are enqueued in different ones of a plurality of call queues that correspond to a skill and each one of which corresponds to a different priority. To simplify the illustrative example of the invention, system 101 is configured to assign each call to only one call queue which corresponds to the skill that the call needs the most. Likewise, each agent's skills are typically prioritized according to his or her level of expertise in that skill, and either agents are enqueued in individual ones of agent queues 130 in their order of expertise or are enqueued in different ones of a plurality of agent queues that correspond to a skill and each one of which corresponds to a different level of expertise. Included among the control programs in a memory (e.g., RAM, ROM, disk, or some other storage device) of ACD system 101 are a call vector 140, an agent vector 150, and a function for estimating in-queue waiting time (EWT) 145. Calls incoming to the call center on lines or trunks 100 are assigned by call vector 140 to different call queues 121-129 based upon the agent skill that they require for their proper handling. EWT 145 computes estimates of how long an incoming call will have to wait in a call queue 121-129, e.g., before being handled by an agent. Agents 106-108 who are available for handling calls are assigned by agent vector 150 to agent queues 131-139 based upon the skills which they possess. Individual calls requiring different skills are handled by agents 106-108 who are individually assigned to different ones of the skills. Call vectoring is described in DEFINITYŽ Communications System Generic 3 Call Vectoring/Expert Agent Selection (EAS) Guide, AT&T publication no. 555-230-520 (Issue Nov. 3, 1993). Skills-based ACD is described in further detail in U.S. Pat. No. 5,206,903. An illustrative EWT function is described in U.S. Pat. No. 5,506,898. An illustrative implementation of agent vectoring is described in U.S. patent application Ser. No. 08/674,477, filed on Jul. 2, 1996, issued as U.S. Pat. No. 5,721,770, on Feb. 24, 1998 and incorporated herein by reference.

According to the invention, agent vector 150 is configured as follows.

As each agent 106-108 logs in at an agent position 102-104, agent vector 150 automatically assigns the agent to handling calls that require one or more of the skills of that agent, by logging the agent into the one or more of the skills. As the call volumes of calls requiring different skills (i.e., call volumes of calls in different call queues 121-129) change, the assignment is periodically recalculated and changed by agent vector 150 as required.

The assignment of an agent to skills is proportional. E.g., an agent may be 30% allocated to one skill and 70% allocated to another skill. This means that, on average, 30% of the agent's work time should require the first skill and the remaining 70% of the agent's work time should require the second skill. An agent will not be logged into a skill if that agent's optimum proportion of calls requiring that skill is determined to be either zero or below some predetermined threshold.

There are two components to a complete solution: 1) An optimization function which calculates the optimum proportions. The optimum proportions are calculated as the solution of a constrained linear optimization problem. This is a well-understood problem, and there are many algorithms for solving this problem. 2) A call-distribution or an agent-vectoring algorithm which distributes calls to agents in the optimum proportions.

The inputs to the linear optimization include a set of levels of priority, or expertise, in each skill for each agent. These numbers represent the "value" to the call center of the agent taking a call that requires that particular skill. The size of the values is not important, but the relative size of the values determines the relative benefit to the call center of the agent taking a call in the skill. E.g., if agent A has a value of 30 in a skill and agent B has a value of 90 in the same skill, then it is three times more desirable for agent B to take a call in that skill than for agent A to take the call.

Optimum operation of the call center may involve minimizing the operating cost of the call center or maximizing the level of service, or it may be defined in terms of other relevant performance characteristics of the call center. The optimization objective determines the values used as inputs to the optimization and some of the parameters of the optimization. The objective may be different for different call centers.

Once the optimum proportions for allocation of agents to skills have been calculated, calls must be distributed to agents so that the call loads match the desired proportions. This can be achieved by storing the percentage of time spent by each agent handling calls in each skill in the last X minutes (or whatever other period of time makes sense) and distributing calls to agents in such a way as to bring the percentages closer to the ideal.

The computations performed by agent vector 150 are based on the following model of the call center of FIG. 1.

2. Modeling a Call Center

2.1 Elements of the Model

The model assumes that a call center has a number of queues, and that each queue is associated with exactly one skill. When calls arrive at a call center, they are placed in queues. Each call is queued in exactly one queue at any given time. This makes sense because the solution presented here removes any need to queue a call to more than one skill at any time.

As agents become available, if there is a call available in one of the call queues corresponding to a skill that the agent is logged into, the first call is taken from one of the call queues and is passed to the agent. It is assumed that the ACD is capable of distributing calls in such a way that a fixed proportion of the agent's workload--either time or number of calls handled--can be allocated to each skill.

The model is restricted to only consider the life of calls coming from queues and serviced by agents. It is only concerned with the average volume of calls coming into the call center to each skill. Measures of performance such as an estimate of the time that a caller should expect to wait in a queue before the call is answered by an agent (EWT) and the length of time that the oldest call in a queue has been waiting (OCW) are related to the rate at which calls enter the call center and the rate at which calls are being serviced, and are not considered in the model.

To model the distribution of calls to agents, individual calls are ignored. It is assumed that calls are like water flowing through pipes and that it is desired to maximize the "value" of the flow of calls through a call center. The behavior of queues is ignored, as queues serve mainly to smooth out fluctuations in the call volume entering a call center.

The main elements of the model are skills, agents, call volumes, and measures of value.

2.2 Measuring Call Volumes

If a call center has n skills numbered 1 to n, and m available agents numbered 1 to m, we define the following notation:

Let Vs be the volume of calls arriving in skill s, for s=1, . . . , n. These volumes are measured by counting the number of calls arriving in each skill in the last x minutes--whatever time period makes sense for the call center.

Let As be the volume of abandoned calls in skill s.

Let Vs,a, be the volume of calls from skill s being handled by agent a, where s=1, . . . , n and a=1, . . . , m.

We also need to take into account the capacity of each agent to handle calls in each skill.

Let Cs,a, be the capacity of agent a to handle calls in skill s, for s=1, . . . , n and a=1, . . . , m. I.e., Cs,a is the (maximum, average) volume of calls that agent a can handle in skill s. These values are measurable positive call volumes. These capacities are measured from historical data by taking the number of calls handled by each agent in each skill over a sufficiently long period and dividing them by the total time that the agent has spent handling those calls in each skill--including after-call work (ACW) time, etc. It may make sense to ignore differences between individual agents and use an average of all agents handling calls in each skill.

Let Rs,a be the proportion of time that agent a spends handling calls from skill s, for s=1, . . . , n and a=1, . . . , m.

The values Vs, Vs,a and Cs,a have units of calls per hour. The Rs,a values are dimensionless.

Note that Vs,a =Cs,a ×Rs,a, for s=1, . . . , n and a=1, . . . , m.

By varying the proportion of time that each agent spends handling calls in each skill, the running of the call center can be optimized to maximize a given objective.

2.3 Constraints

These quantities defined so far satisfy the following relationships: ##EQU1## I.e., the volume of calls coming into a skill equals the sum of the total volume of calls handled by agents for that skill plus the volume of calls abandoned. This constraint can be rewritten in terms of the proportions Rs,a as follows: ##EQU2## I.e., an agent cannot spend a negative proportion of his or her time on calls from any skill. ##EQU3## I.e., the relative proportions of time that an agent spends handling calls in each skill cannot add up to more than one.

2.4 Measuring Call Center Performance

To optimize the operation of a call center, we need to assign an estimate of value to each call handled. How the value of each call is determined will be different for each call center.

The values of calls handled are, in general, different for different skills and also depend on which agent handles the call. E.g., it is of more value for an agent who is well-trained in a skill to handle calls for that skill, than one who has little or no training for the skill. To model this, we define a value for each agent taking calls in a particular skill:

Let Bs,a be the benefit or value to the call center of a call from skill s being handled by agent a, for s=1, . . . , n and a=1, . . . , m.

Bs,a is a per-call benefit and does not take into account how long it takes for the agent to handle the call. Bs,a may be thought of as the expertise that agent a has in skill s. Note that only the relative sizes of these values are important for the purpose of optimizing the call center.

How the Bs,a values are chosen depends on the call center's purpose. They may represent (average) dollars of profit per call, or a negative value representing the cost of a call, etc. These quantities can be measured or estimated.

A better measure of an agent's performance also takes into account the volume of calls that the agent can handle in each skill:

Let Ls,a =Cs,a ×Bs,a, for s=1, . . . , n and a=1, . . . , m.

Ls,a is a measure of the benefit to the call center of agent a taking calls in skill s per unit time. E.g., if L2,5 =25 and L3,1 =50, then it is twice as valuable for agent 1 to spend an hour taking calls in skill 3 as it is for agent 5 to spend an hour taking calls in skill 2. Ls,a is a measure of the expertise of the agent in the particular skill.

Since Cs,a is a measurable quantity, defining Ls,a for each agent/skill pair is equivalent to defining Bs,a for each agent/skill pair. Either of these sets of values may be used to define the objective function for a call center. The Ls,a values may also be chosen to be values that can be measured, such as profit in dollars per hour.

It is also convenient to define a penalty for abandoned calls:

Let Ps be the penalty for an abandoned call in skill s, for s=1, . . . , n.

The overall efficiency of the call center can be measured by the quantity: ##EQU4## where B represents the total benefit to the call center of individual ones of the agents handling calls requiring individual ones of the skills.

2.5 Other Performance Measures

Customers typically use a variety of metrics to measure call-center performance. These include oldest-call waiting (OCW), average speed of answer (ASA), and service level. This model does not take into account these measures because they can all be viewed as indicators of the percentage of utilization of the resources available for handling calls in the given skill. E.g., if the EWT for sales is too high, then this indicates that there are insufficient resources allocated to sales, i.e., the estimate of call volume for sales needs to be increased.

This model does not directly take into account other measures of performance such as oldest call waiting (OCW) times, service levels, or queue lengths. These measures are all related to the ratio of the volume of calls coming into a skill and the capacity of the call center to handle calls in each skill. Queuing theory gives some relationships between these other measures of performance and volumes of calls.

2.6 Some Ideas from Queuing Theory

Queuing theory is a complex subject, and the model presented here deliberately ignores the details of what is happening in queues, but it is useful to note some elementary properties of queues to see how the model can be used to control the behavior of call center queues. For queuing theory principles relevant hereto, see, e.g., see W. Stallings, Data and Computer Communications (3d ed.) Macmillan Pub. Co (1988), Appendix A.

Queuing theory states that the average waiting time in a first-in, first-out (FIFO) queue is approximately proportional to ##EQU5## and the average number of calls in a queue is proportional to ##EQU6## where m is the number of agents, p is the average fraction of time that each agent is busy, and b is the probability that all agents are busy. These values are approximate because they assume that all agents are only handling one skill. There are two important things to note here:

1. As the utilization approaches 100%, the average queue length and average waiting time approach infinity. (Assuming, of course, that no calls are abandoned and that there are infinitely many trunks and infinite queuing capacity.)

2. Full utilization of call center resources is not possible without very long queue lengths and very patient customers. (About 80-90% should be realistically achievable. As the utilization reaches 80-90%, the queue lengths and waiting times start to climb very rapidly. The exact point at which this happens depends on the details of the probability distribution of the mean time between agents becoming available, which varies between call centers and skills.)

This confirms what every call center supervisor already knows: that the average waiting time and the number of calls in a queue are sensitive indicators of the utilization of the resources presently allocated to a skill.

3. Optimizing Call Center Performance

Given the above, optimization of call center performance reduces to the following optimization problem: ##EQU7##

This problem has an exact solution which can be calculated using the well-known Simplex Algorithm (See, e.g., R. Sedgewick, Algorithms, Addison Wesley (1946), Chapter 38).

The values Vs represent the call volumes entering the call center in each skill.

The values Cs,a are measurable values which represent the volume of calls that each agent can handle in each skill.

The values Ls,a and Ps are determined by the call center supervisor. These values depend on the criteria chosen to measure the performance of the call center. If the Ls,a and Ps values are chosen sensibly, the allocation of calls to agents can be done automatically. These values can even be tied to quantities that can be automatically tracked.

The values Rs,a are the values to be optimized. In most call centers, not all agents will be expected to handle calls in all skills, so some of these values may be set at 0, which means they can be ignored and left out of the optimization process.

4. Adding More Flexibility

The main aim here is to provide a means to automatically allocate call center resources where they are needed. It is the call center supervisor's responsibility to decide the relative priorities of the different skills. To make it easier for the supervisor to control where resources are allocated, per-skill weights Ws may be added to the objective function: ##EQU8##

The intention is that the skill levels Ls,a should not need to change very often, as they represent expertise (levels of ability) of the agents in each skill. The skill weightings are intended to be changed in response to changing conditions. This gives the call center supervisor a means of adjusting the automatic control and overriding the priorities determined by the skill levels. E.g., if the level of service for the skill "complaints" is unacceptable and the supervisor is prepared to sacrifice service in other skills, he or she can increase the weighting for "complaints" in order to make the system allocate more resources to "complaints".

5. Limitations of the Model

This model does not take into account all of the complexity of real call centers. E.g., it assumes that once a call is queued, it is either answered by an agent or the caller will abandon the call. It does not take into account calls answered by voice-response units.

Another thing to note is that the optimum solution produced by this model may not be unique. E.g., if there are two agents, Dana and Fox, with the same level of skill in "Insurance Enquiries" and they are not needed for any other skills, then if the volume of calls in "Insurance Enquiries" is not high, the same optimum performance can be achieved by allocating half of the calls to Dana and half of the calls to Fox or all of the calls to Dana and none of the calls to Fox. If there is a choice, the Simplex Algorithm is likely to allocate all of the calls to one of the agents and none of the calls to the other. It does not ensure that the call loads are fairly distributed to agents. Additional constraints are needed to ensure fair distribution of calls.

This model ignores the behavior of the skill queues. It collapses all of the queues' properties into two numbers per queue: volume of calls and volume of abandoned calls. This means that the model cannot be used to directly to calculate optimum skill allocations for minimizing, for example, average speed of answer (ASA) over all queues. The only information that the model has about what is happening in each queue is the call volume and the number of abandoned calls. Abandoned calls are a poor indicator of poor service, because it is better to deal with long wait times in a queue before the number of abandoned calls becomes too high.

It is useful to add some penalty terms to the optimization representing the cost of poor ASA. These terms should be non-linear and have not been included in order to keep the problem simple and easily solvable. Another way to tie ASA into the model is to make the skill weights Ws dependent on the queue length.

6. The Agent Vector

Given the above-described model for optimizing call-center performance, agent vector 150 operates as follows.

Whenever any agent 106-108 logs in at an agent position 102-104, as indicated at step 200 of FIG. 2, agent vector 150 retrieves the agent's skills and levels of expertise from a database of system 101, at step 202, and logs the agent into each of the agent's skills at the corresponding level of expertise, at step 204, and then ends, at step 206. Similarly, whenever any agent 106-108 logs off at an agent position 102-104, as indicated at step 300 of FIG. 3, agent vector 150 logs the agent out of each skill into which the agent is logged in, at step 302, and then ends, at step 304.

Periodically, agent vector 150 is invoked to perform a benefit optimization of the call center of FIG. 1. This function of agent vector 150 is diagrammed in FIG. 4. Upon its invocation, at step 400, agent vector 150 retrieves predetermined values of optimization parameters from CMS 110, at step 402. These are the values that are preestablished by the call center supervisor, such as the values for the measure of benefit to the call center of each agent taking calls in each skill per unit of time (Ls,a) and the penalty for an abandoned call in each skill (Ps) Agent vector 150 then uses measured data that is stored by CMS 110 to determine (measure) the present values of other optimization parameters, at step 404. These are the values for the volume of calls arriving for each skill (Vs), the volume of abandoned calls for each skill (As), the capacity of each agent to handle calls in each skill (Cs,a), and the actual proportion of time that each agent spends handling calls for each skill (actual Rs,a). Agent vector 150 then uses the parameter values to perform the benefit-optimization function on the predetermined call-center performance characteristic (e.g., maximize B) that was presented in Section 3 above, to obtain the optimum proportion of work that each agent spends handling calls for each skill (optimum Rs,a), for each agent and each skill, at step 406.

Vector 150 then compares the actual Rs,a with the optimum Rs,a for each agent and each skill and adjusts the agents' call-handling priorities in order to bring the actual Rs,a values more in line with the optimum Rs,a values. Vector 150 selects a first agent (a), at step 408, and a first skill (s), at step 410, and compares the actual Rs,a with the optimum Rs,a to determine if the actual proportion of work that the selected agent spends handling calls for the selected skill exceeds the optimum, at step 412. If the actual work proportion does exceed the optimum work proportion, vector 150 checks whether the selected agent is logged into the selected skill, at step 414, and if so, logs the selected agent out of the selected skill, at step 416.

Thereafter, or if it is determined at step 412 that the actual work proportion does not exceed the optimum work proportion, vector 150 determines if the optimum proportion of work that the selected agent spends handling calls for the selected skill exceeds the actual proportion of work that the selected agent spends handling calls for the selected skill, at step 418. If the optimum work proportion does exceed the actual work proportion, vector 150 checks whether the selected agent is logged into the selected skill, at step 420, and if not, logs the selected agent into the selected skill, at step 422.

Thereafter, or if it is determined at step 418 that the optimum work proportion does not exceed the actual work proportion, vector 150 checks whether it has done the optimization for each skill of the selected agent, at step 424. If optimization has not been done for each skill of the selected agent, vector 150 selects the next skill of the selected agent, at step 426, and returns to step 412 to perform the optimization for this next skill. If and when optimization has been done for each skill of the selected agent, vector 150 checks whether it has done the optimization for each logged-in agent, at step 428, If optimization has not been done for each logged-in agent, vector 150 selects the next logged in agent, at step 430, and returns to step 410 to perform the optimization for each skill of this next agent. If and when optimization has been done for all logged in agents, vector 150 ends its operation, at step 432, until it is invoked again at step 200, 300, or 400.

Of course, various changes and modifications to the illustrative embodiment described above will be apparent to those skilled in the art. For example, the optimization of call-center performance may be drastically simplified to reassign agents among skills only in response to actual or anticipated emergency service threshold being reached.

In this simplified arrangement, agents are pre-assigned to all the skills that they have been trained to handle, but only the skills in which they are scheduled to work are given high preference (expertise) levels, meaning that under normal circumstances they only handle calls from their scheduled skills. Their other, backup, skills have low preference levels, and only come into effect when there is a service level emergency.

Each skill may have one or more emergency service level thresholds administered. Exceeding these thresholds is an indication that there is a service level emergency and that the skill requires additional staffing.

Under normal conditions, (i.e., no service level emergencies), when an agent becomes available to take a call, the ACD's normal criteria for choosing a call are used. (These criteria typically include the agent's skill preference levels or work allocation, call priorities, and the time that each call has been in queue, etc.)

If the agent becomes available when one of his/her administered skills has a service level emergency, the emergency overrides all other criteria, and the agent gets a call from the skill with the emergency condition. If more than one of the agent's administered skills has a service level emergency, a number of options are available. For example, the traditional criteria, such as skill preference level, can be used to select one of the emergency skills.

At the opposite end of the spectrum, each skill may also have a low threshold administered to cater to situations where the skill has been overstaffed. In this situation, agent call handling priorities are adjusted to redirect agents away from skills with service times which are below the low threshold.

This arrangement has the ability to detect and resolve potential service problems rapidly and automatically. Enough agents are diverted to handle calls from the emergency queue, sufficient to bring the service time back within the skill's threshold, at which time call allocation returns to normal. If a predictor of future waiting times is used as the threshold criterion, potential service problems can be dealt with before any call has actually exceeded the wait time threshold.

Such changes and modifications can be made without departing from the spirit and the scope of the invention and without diminishing its attendant advantages. It is therefore intended that such changes and modifications be covered by the following claims.

Patent Citations
Cited PatentFiling datePublication dateApplicantTitle
US4885686 *Jan 12, 1987Dec 5, 1989American Telephone And Telegraph At&T Bell LaboratoriesMethods and apparatus for efficient resource allocation
US5031089 *Dec 30, 1988Jul 9, 1991United States Of America As Represented By The Administrator, National Aeronautics And Space AdministrationDynamic resource allocation scheme for distributed heterogeneous computer systems
US5148365 *Aug 15, 1989Sep 15, 1992Dembo Ron SSystem for allocating available resources in a physical system
US5185715 *Mar 30, 1990Feb 9, 1993Hughes Aircraft CompanyData processing systems and methods for linear programming
US5185780 *Oct 12, 1990Feb 9, 1993Tex CorporationMethod for predicting agent requirements in a force management system
US5206903 *Dec 26, 1990Apr 27, 1993At&T Bell LaboratoriesAutomatic call distribution based on matching required skills with agents skills
US5299260 *Jul 29, 1993Mar 29, 1994Unifi Communications CorporationTelephone call handling system
US5309513 *Jul 2, 1992May 3, 1994Rockwell International CorporationTelephone system with ubiquitous agents
US5335269 *Mar 12, 1992Aug 2, 1994Rockwell International CorporationTwo dimensional routing apparatus in an automatic call director-type system
US5467391 *Jul 14, 1994Nov 14, 1995Digital Systems International, Inc.Integrated intelligent call blending
US5499291 *Jan 14, 1993Mar 12, 1996At&T Corp.Arrangement for automating call-center agent-schedule-notification and schedule-adherence functions
US5506898 *Jul 12, 1994Apr 9, 1996At&T Corp.Expected wait-time indication arrangement
US5594791 *Oct 5, 1994Jan 14, 1997Inventions, Inc.Method and apparatus for providing result-oriented customer service
US5721770 *Jul 2, 1996Feb 24, 1998Lucent Technologies Inc.Agent vectoring programmably conditionally assigning agents to various tasks including tasks other than handling of waiting calls
EP0740450A2 *Apr 22, 1996Oct 30, 1996International Business Machines CorporationMethod and apparatus for skill-based routing in a call center
GB2293724A * Title not available
WO1996022650A1 *Jan 18, 1996Jul 25, 1996British TelecommAnswering telephone calls
Non-Patent Citations
Reference
1 *D. Harvey, S. Hogan, J. Payseur, Call Center Solutions , AT&T Technical Journal, 70(1991) Sep./Oct. No. 5, Short Hills, NJ, (US), pp.36 44.
2D. Harvey, S. Hogan, J. Payseur, Call Center Solutions, AT&T Technical Journal, 70(1991) Sep./Oct. No. 5, Short Hills, NJ, (US), pp.36-44.
3 *IEX , Computer Telephony, vol. 5, Issue 8, Aug. 1996, p. 138.
4IEX, Computer Telephony, vol. 5, Issue 8, Aug. 1996, p. 138.
5 *K. Hassler, C. Jones, J. Kohler, R. Nalbone, Revolutionizing DEFINITY R Call Center in the 1990s , AT&T Technical Journal, 74(1995) Jul./Aug., No. 4, New York, (US) pp. 64 73.
6K. Hassler, C. Jones, J. Kohler, R. Nalbone, Revolutionizing DEFINITYR Call Center in the 1990s, AT&T Technical Journal, 74(1995) Jul./Aug., No. 4, New York, (US) pp. 64-73.
Referenced by
Citing PatentFiling datePublication dateApplicantTitle
US6052460 *Dec 17, 1997Apr 18, 2000Lucent Technologies Inc.Arrangement for equalizing levels of service among skills
US6088441 *Dec 17, 1997Jul 11, 2000Lucent Technologies Inc.Arrangement for equalizing levels of service among skills
US6130942 *Oct 30, 1998Oct 10, 2000Ericsson Inc.Skills-based automatic call distribution system
US6163607 *Nov 3, 1998Dec 19, 2000Avaya Technology Corp.Optimizing call-center performance by using predictive data to distribute agents among calls
US6173053 *Apr 9, 1998Jan 9, 2001Avaya Technology Corp.Optimizing call-center performance by using predictive data to distribute calls among agents
US6188673 *Sep 2, 1997Feb 13, 2001Avaya Technology Corp.Using web page hit statistics to anticipate call center traffic
US6192122 *Feb 12, 1998Feb 20, 2001Avaya Technology Corp.Call center agent selection that optimizes call wait times
US6272544 *Sep 8, 1998Aug 7, 2001Avaya Technology CorpDynamically assigning priorities for the allocation of server resources to completing classes of work based upon achievement of server level goals
US6278777Feb 17, 2000Aug 21, 2001Ser Solutions, Inc.System for managing agent assignments background of the invention
US6292550 *Jun 1, 1998Sep 18, 2001Avaya Technology Corp.Dynamic call vectoring
US6310951 *Sep 25, 1998Oct 30, 2001Ser Solutions, Inc.Reassignment of agents
US6324282Mar 2, 2000Nov 27, 2001Knowlagent, Inc.Method and system for delivery of individualized training to call center agents
US6330326 *Mar 27, 1998Dec 11, 2001At&T Corp.Dynamic staffing of service centers to provide substantially zero-delay service
US6347139Dec 6, 1999Feb 12, 2002Avaya Technology Corp.System for automatically routing calls to call center agents in an agent surplus condition based on agent occupancy
US6389400 *May 3, 1999May 14, 2002Sbc Technology Resources, Inc.System and methods for intelligent routing of customer requests using customer and agent models
US6424709Mar 22, 1999Jul 23, 2002Rockwell Electronic Commerce Corp.Skill-based call routing
US6459787Sep 10, 2001Oct 1, 2002Knowlagent, Inc.Method and system for delivery of individualized training to call center agents
US6510221Dec 6, 1999Jan 21, 2003Avaya Technology Corp.System for automatically routing calls to call center agents in an agent surplus condition based on delay probabilities
US6535600 *Dec 6, 1999Mar 18, 2003Avaya Technology Corp.System for automatically routing calls to call center agents in an agent surplus condition based on service levels
US6535601 *Aug 27, 1998Mar 18, 2003Avaya Technology Corp.Skill-value queuing in a call center
US6553114Dec 6, 1999Apr 22, 2003Avaya Technology Corp.System for automatically predicting call center agent work time in a multi-skilled agent environment
US6587556Feb 25, 2000Jul 1, 2003Teltronics, Inc.Skills based routing method and system for call center
US6594470Oct 28, 1999Jul 15, 2003Nortel Networks LimitedSystem and method for remote management of call center operations
US6603852 *Oct 13, 1998Aug 5, 2003Fujitsu LimitedOperator call-fielding scenario system
US6603854Feb 25, 2000Aug 5, 2003Teltronics, Inc.System and method for evaluating agents in call center
US6628777Nov 16, 1999Sep 30, 2003Knowlagent, Inc.Method and system for scheduled delivery of training to call center agents
US6631399 *Aug 4, 1999Oct 7, 2003Open Port Technology, Inc.System and method for automated received message handling and distribution
US6661889 *Jan 18, 2000Dec 9, 2003Avaya Technology Corp.Methods and apparatus for multi-variable work assignment in a call center
US6697858Aug 14, 2000Feb 24, 2004Telephony@WorkCall center
US6707904Feb 25, 2000Mar 16, 2004Teltronics, Inc.Method and system for collecting reports for call center monitoring by supervisor
US6724887Jan 24, 2000Apr 20, 2004Verint Systems, Inc.Method and system for analyzing customer communications with a contact center
US6741698 *Jan 27, 2000May 25, 2004Avaya Technology Corp.Call management system using dynamic threshold adjustment
US6763104Feb 24, 2000Jul 13, 2004Teltronics, Inc.Call center IVR and ACD scripting method and graphical user interface
US6766012Oct 20, 1999Jul 20, 2004Concerto Software, Inc.System and method for allocating agent resources to a telephone call campaign based on agent productivity
US6771760 *Sep 20, 1999Aug 3, 2004International Business Machines CorporationCallback imitation as incoming calls
US6771764 *Jan 26, 2000Aug 3, 2004Rockwell Electronic Commerce Corp.Schedule based transaction routing
US6775377Jul 18, 2002Aug 10, 2004Knowlagent, Inc.Method and system for delivery of individualized training to call center agents
US6778643Mar 21, 2000Aug 17, 2004Sbc Technology Resources, Inc.Interface and method of designing an interface
US6788780 *Feb 17, 1999Sep 7, 2004Siemens AktiengesellschaftCommunications apparatus
US6804341 *May 2, 2001Oct 12, 2004Bellsouth Intellectual Property Corp.System and method for providing no answer detail service for telephone calls that are not completed
US6804345 *Jan 27, 2000Oct 12, 2004At&T CorpVirtual contact center with flexible staffing control
US6853721Sep 30, 2002Feb 8, 2005Rockwell Electronic Commerce Technologies, LlcContact center autopilot architecture
US6853966Apr 30, 2002Feb 8, 2005Sbc Technology Resources, Inc.Method for categorizing, describing and modeling types of system users
US6856680 *Sep 24, 2001Feb 15, 2005Rockwell Electronic Commerce Technologies, LlcContact center autopilot algorithms
US6859529Feb 25, 2002Feb 22, 2005Austin Logistics IncorporatedMethod and system for self-service scheduling of inbound inquiries
US6870926 *Nov 6, 2001Mar 22, 2005Rockwell Electronic Commerce Technologies, LlcMethod of optimizing call center resources based upon statistics
US6891946 *Jan 25, 2002May 10, 2005Walgreen, Co.Automated phone priorities
US6914975Feb 21, 2002Jul 5, 2005Sbc Properties, L.P.Interactive dialog-based training method
US6947988Aug 11, 2000Sep 20, 2005Rockwell Electronic Commerce Technologies, LlcMethod and apparatus for allocating resources of a contact center
US6973176Sep 30, 2003Dec 6, 2005Avaya Technology Corp.Method and apparatus for rotating auto reserve agents
US7027586Dec 18, 2003Apr 11, 2006Sbc Knowledge Ventures, L.P.Intelligently routing customer communications
US7035808 *Oct 20, 1999Apr 25, 2006Avaya Technology Corp.Arrangement for resource and work-item selection
US7039176Jul 9, 2001May 2, 2006Telephony@WorkCall center administration manager with rules-based routing prioritization
US7043193Aug 15, 2000May 9, 2006Knowlagent, Inc.Versatile resource computer-based training system
US7050566Jun 13, 2003May 23, 2006Assurant, Inc.Call processing system
US7054434Jun 6, 2003May 30, 2006Austin Logistics IncorporatedSystem and method for common account based routing of contact records
US7058589 *Dec 17, 1999Jun 6, 2006Iex CorporationMethod and system for employee work scheduling
US7065201Jul 31, 2001Jun 20, 2006Sbc Technology Resources, Inc.Telephone call processing in an interactive voice response call management system
US7068774Feb 25, 2000Jun 27, 2006Harris CorporationIntegrated acd and ivr scripting for call center tracking of calls
US7076049Jul 2, 2004Jul 11, 2006Sbc Technology Resources, Inc.Method of designing a telecommunications call center interface
US7086007May 26, 2000Aug 1, 2006Sbc Technology Resources, Inc.Method for integrating user models to interface design
US7103173Mar 12, 2002Sep 5, 2006Austin Logistics IncorporatedSystem and method for preemptive goals based routing of contact records
US7103562 *May 17, 2002Sep 5, 2006Bay Bridge Decision Technologies, Inc.System and method for generating forecasts and analysis of contact center behavior for planning purposes
US7106850Jan 8, 2001Sep 12, 2006Aastra Intecom Inc.Customer communication service system
US7110525 *Jun 25, 2002Sep 19, 2006Toby HellerAgent training sensitive call routing system
US7120239 *Aug 17, 2004Oct 10, 2006Bellsouth Intellectual Property Corp.System and method for providing no answer detail service for telephone calls that are not completed
US7133520 *Apr 27, 1999Nov 7, 2006Rockwell Electronic Commerce Technologies, LlcDynamic skill-based call routing
US7139369Aug 29, 2002Nov 21, 2006Sbc Properties, L.P.Interface and method of designing an interface
US7142662Jul 9, 2001Nov 28, 2006Austin Logistics IncorporatedMethod and system for distributing outbound telephone calls
US7158628Aug 20, 2003Jan 2, 2007Knowlagent, Inc.Method and system for selecting a preferred contact center agent based on agent proficiency and performance and contact center state
US7158629Jun 7, 2006Jan 2, 2007Austin Logistics IncorporatedSystem and method for preemptive goals based routing of contact records
US7158909Mar 31, 2004Jan 2, 2007Balboa Instruments, Inc.Method and system for testing spas
US7170990 *Jun 18, 2002Jan 30, 2007Avaya Technology Corp.Autonomous dispatcher method and apparatus
US7174010Sep 20, 2002Feb 6, 2007Knowlagent, Inc.System and method for increasing completion of training
US7184541Dec 11, 2003Feb 27, 2007General Electric Capital CorporationMethod and apparatus for selecting an agent to handle a call
US7200219Feb 10, 1999Apr 3, 2007Avaya Technology Corp.Dynamically allocating server resources to competing classes of work based upon achievement of service goals
US7224790May 26, 2000May 29, 2007Sbc Technology Resources, Inc.Method to identify and categorize customer's goals and behaviors within a customer service center environment
US7239692Nov 20, 2006Jul 3, 2007Austin Logistics IncorporatedMethod and system for distributing outbound telephone calls
US7295669Jan 21, 1999Nov 13, 2007Avaya Technology Corp.Call center telephone and data flow connection system
US7305070Jan 30, 2002Dec 4, 2007At&T Labs, Inc.Sequential presentation of long instructions in an interactive voice response system
US7336779Mar 15, 2002Feb 26, 2008Avaya Technology Corp.Topical dynamic chat
US7359503 *Jan 13, 2005Apr 15, 2008Verizon Services Corp.Method of and system for providing services in a communications network
US7366293Mar 2, 2001Apr 29, 2008Oracle Sytems CorporationCall center administration manager
US7373309 *Mar 26, 2002May 13, 2008International Business Machines CorporationSystem and method for calculating and displaying estimated wait times for transaction request based on the skill required to process the transaction request
US7379537Aug 13, 2002May 27, 2008At&T Knowledge Ventures, L.P.Method and system for automating the creation of customer-centric interfaces
US7406171Dec 19, 2003Jul 29, 2008At&T Delaware Intellectual Property, Inc.Agent scheduler incorporating agent profiles
US7406515 *Jun 27, 2000Jul 29, 2008Aspect CommunicationsSystem and method for automated and customizable agent availability and task assignment management
US7415417Mar 15, 2002Aug 19, 2008Avaya Technology Corp.Presence awareness agent
US7428303Apr 6, 2006Sep 23, 2008Aastra Intecom Inc.Customer communication service system
US7453994Oct 22, 2007Nov 18, 2008At&T Labs, Inc.Sequential presentation of long instructions in an interactive voice response system
US7469047Mar 8, 2005Dec 23, 2008Harris CorporationIntegrated ACD and IVR scripting for call center tracking of calls
US7499844Dec 19, 2003Mar 3, 2009At&T Intellectual Property I, L.P.Method and system for predicting network usage in a network having re-occurring usage variations
US7502460Jun 6, 2007Mar 10, 2009Austin Logistics IncorporatedMethod and system for distributing outbound telephone calls
US7511606May 18, 2005Mar 31, 2009Lojack Operating Company LpVehicle locating unit with input voltage protection
US7526731Jun 7, 2006Apr 28, 2009At&T Labs, Inc.Method for integrating user models to interface design
US7539297Dec 19, 2003May 26, 2009At&T Intellectual Property I, L.P.Generation of automated recommended parameter changes based on force management system (FMS) data analysis
US7551602Dec 19, 2003Jun 23, 2009At&T Intellectual Property I, L.P.Resource assignment in a distributed environment
US7567653Mar 22, 2005Jul 28, 2009Avaya Inc.Method by which call centers can vector inbound TTY calls automatically to TTY-enabled resources
US7568038Dec 17, 2003Jul 28, 2009Oracle International CorporationCall centers for providing customer services in a telecommunications network
US7593521Dec 16, 2005Sep 22, 2009Assurant, Inc.Call processing system
US7616755Dec 19, 2003Nov 10, 2009At&T Intellectual Property I, L.P.Efficiency report generator
US7620169Jun 17, 2002Nov 17, 2009Avaya Inc.Waiting but not ready
US7657021Feb 14, 2005Feb 2, 2010Avaya Inc.Method and apparatus for global call queue in a global call center
US7657263 *Mar 21, 2002Feb 2, 2010Cisco Technology, Inc.Method and system for automatic call distribution based on customized logic relating to agent behavior
US7676034 *Mar 5, 2004Mar 9, 2010Wai WuMethod and system for matching entities in an auction
US7711104Sep 20, 2004May 4, 2010Avaya Inc.Multi-tasking tracking agent
US7715546Feb 9, 2004May 11, 2010Austin Logistics IncorporatedSystem and method for updating contact records
US7729490Feb 12, 2004Jun 1, 2010Avaya Inc.Post-termination contact management
US7734032Mar 31, 2004Jun 8, 2010Avaya Inc.Contact center and method for tracking and acting on one and done customer contacts
US7734783 *Mar 21, 2006Jun 8, 2010Verint Americas Inc.Systems and methods for determining allocations for distributed multi-site contact centers
US7739149 *Sep 20, 2004Jun 15, 2010Proficient Systems, Inc.Systems and methods to facilitate selling of products and services
US7747705May 8, 2007Jun 29, 2010Avaya Inc.Method to make a discussion forum or RSS feed a source for customer contact into a multimedia contact center that is capable of handling emails
US7751552Dec 20, 2005Jul 6, 2010At&T Intellectual Property I, L.P.Intelligently routing customer communications
US7752230Oct 6, 2005Jul 6, 2010Avaya Inc.Data extensibility using external database tables
US7756261Feb 29, 2008Jul 13, 2010MCI Communications Corporation & Verizon Communications Inc.Method of and system for providing services in a communications network
US7770175Sep 26, 2003Aug 3, 2010Avaya Inc.Method and apparatus for load balancing work on a network of servers based on the probability of being serviced within a service time goal
US7779042Aug 8, 2005Aug 17, 2010Avaya Inc.Deferred control of surrogate key generation in a distributed processing architecture
US7787609Oct 6, 2005Aug 31, 2010Avaya Inc.Prioritized service delivery based on presence and availability of interruptible enterprise resources with skills
US7792726 *Dec 31, 2007Sep 7, 2010International Business Machines CorporationReception management system for assigning transaction requests to operator terminals
US7809127 *Jul 28, 2005Oct 5, 2010Avaya Inc.Method for discovering problem agent behaviors
US7817796Apr 27, 2005Oct 19, 2010Avaya Inc.Coordinating work assignments for contact center agents
US7822587Oct 3, 2005Oct 26, 2010Avaya Inc.Hybrid database architecture for both maintaining and relaxing type 2 data entity behavior
US7835514Sep 18, 2006Nov 16, 2010Avaya Inc.Provide a graceful transfer out of active wait treatment
US7836405Mar 17, 2009Nov 16, 2010At&T Labs, Inc.Method for integrating user models to interface design
US7844504Sep 25, 2000Nov 30, 2010Avaya Inc.Routing based on the contents of a shopping cart
US7869586Mar 30, 2007Jan 11, 2011Eloyalty CorporationMethod and system for aggregating and analyzing data relating to a plurality of interactions between a customer and a contact center and generating business process analytics
US7881450Sep 15, 2005Feb 1, 2011Avaya Inc.Answer on hold notification
US7885401 *Mar 29, 2004Feb 8, 2011Avaya Inc.Method and apparatus to forecast the availability of a resource
US7907719Aug 21, 2006Mar 15, 2011At&T Labs, Inc.Customer-centric interface and method of designing an interface
US7916858 *Sep 18, 2006Mar 29, 2011Toby HellerAgent training sensitive call routing system
US7920552Apr 30, 2009Apr 5, 2011At&T Intellectual Property I, L.P.Resource assignment in a distributed environment
US7936867Aug 15, 2006May 3, 2011Avaya Inc.Multi-service request within a contact center
US7949121Mar 1, 2005May 24, 2011Avaya Inc.Method and apparatus for the simultaneous delivery of multiple contacts to an agent
US7949123Nov 30, 2004May 24, 2011Avaya Inc.Wait time predictor for long shelf-life work
US7953859Jun 3, 2004May 31, 2011Avaya Inc.Data model of participation in multi-channel and multi-party contacts
US7962356 *May 31, 2006Jun 14, 2011Invision Software AgStaff scheduling
US7962644Aug 28, 2002Jun 14, 2011Oracle International CorporationSystems and methods for handling a plurality of communications
US7979518Sep 14, 2004Jul 12, 2011Mci Communications CorporationIntelligent call platform for an intelligent distributed network
US7995717May 18, 2005Aug 9, 2011Mattersight CorporationMethod and system for analyzing separated voice data of a telephonic communication between a customer and a contact center by applying a psychological behavioral model thereto
US8000989Mar 31, 2004Aug 16, 2011Avaya Inc.Using true value in routing work items to resources
US8015042 *Sep 28, 2006Sep 6, 2011Verint Americas Inc.Methods for long-range contact center staff planning utilizing discrete event simulation
US8023636Mar 31, 2005Sep 20, 2011Sivox Partners, LlcInteractive dialog-based training method
US8023639Mar 28, 2008Sep 20, 2011Mattersight CorporationMethod and system determining the complexity of a telephonic communication received by a contact center
US8036348Oct 14, 2008Oct 11, 2011At&T Labs, Inc.Sequential presentation of long instructions in an interactive voice response system
US8041023 *Sep 29, 2000Oct 18, 2011Aspect Software, Inc.System and method of using a phone to access information in a call center
US8068595Oct 31, 2007Nov 29, 2011Intellisist, Inc.System and method for providing a multi-modal communications infrastructure for automated call center operation
US8073129Oct 3, 2005Dec 6, 2011Avaya Inc.Work item relation awareness for agents during routing engine driven sub-optimal work assignments
US8094790Mar 1, 2006Jan 10, 2012Mattersight CorporationMethod and software for training a customer service representative by analysis of a telephonic interaction between a customer and a contact center
US8094803May 18, 2005Jan 10, 2012Mattersight CorporationMethod and system for analyzing separated voice data of a telephonic communication between a customer and a contact center by applying a psychological behavioral model thereto
US8094804Sep 26, 2003Jan 10, 2012Avaya Inc.Method and apparatus for assessing the status of work waiting for service
US8103961Oct 6, 2010Jan 24, 2012At&T Labs, Inc.Method for integrating user models to interface design
US8116237Sep 26, 2008Feb 14, 2012Avaya Inc.Clearing house for publish/subscribe of status data from distributed telecommunications systems
US8116445Apr 3, 2007Feb 14, 2012Intellisist, Inc.System and method for monitoring an interaction between a caller and an automated voice response system
US8116446Oct 3, 2005Feb 14, 2012Avaya Inc.Agent driven work item awareness for tuning routing engine work-assignment algorithms
US8126133 *Apr 1, 2004Feb 28, 2012Liveops, Inc.Results-based routing of electronic communications
US8131524May 27, 2008Mar 6, 2012At&T Intellectual Property I, L.P.Method and system for automating the creation of customer-centric interfaces
US8170197 *Mar 17, 2005May 1, 2012Intellisist, Inc.System and method for providing automated call center post-call processing
US8175254 *Apr 23, 2009May 8, 2012Avaya Inc.Prediction of threshold exceptions based on real time operating information
US8175258May 18, 2006May 8, 2012Austin Logistics IncorporatedSystem and method for common account based routing of contact records
US8209210Feb 6, 2008Jun 26, 2012International Business Machines CorporationSystem and method for calculating and displaying estimated wait times for transaction request based on the skill required to process the transaction request
US8229101 *Sep 30, 2004Jul 24, 2012Virtual Hold Technology, LlcPunctuality call center metric
US8234141Feb 22, 2005Jul 31, 2012Avaya Inc.Dynamic work assignment strategies based on multiple aspects of agent proficiency
US8238541Jan 31, 2006Aug 7, 2012Avaya Inc.Intent based skill-set classification for accurate, automatic determination of agent skills
US8306212Feb 19, 2010Nov 6, 2012Avaya Inc.Time-based work assignments in automated contact distribution
US8306213Nov 22, 2011Nov 6, 2012Google Inc.Skill and level assignment via concentric inlaid circles
US8340274 *Dec 22, 2008Dec 25, 2012Genesys Telecommunications Laboratories, Inc.System for routing interactions using bio-performance attributes of persons as dynamic input
US8346942Jun 18, 2009Jan 1, 2013Oracle International CorporationCall centers for providing customer services in a telecommunications network
US8359222Sep 26, 2011Jan 22, 2013Bay Bridge Technologies, Inc.System and method for generating forecasts and analysis of contact center behavior for planning purposes
US8385532May 12, 2008Feb 26, 2013Avaya Inc.Real-time detective
US8385533Sep 21, 2009Feb 26, 2013Avaya Inc.Bidding work assignment on conference/subscribe RTP clearing house
US8411843Oct 4, 2005Apr 2, 2013Avaya Inc.Next agent available notification
US8422659Aug 13, 2009Apr 16, 2013Assurant, Inc.Call processing system
US8442197Mar 30, 2006May 14, 2013Avaya Inc.Telephone-based user interface for participating simultaneously in more than one teleconference
US8457296Nov 28, 2011Jun 4, 2013Intellisist, Inc.System and method for processing multi-modal communications during a call session
US8457300May 7, 2010Jun 4, 2013Avaya Inc.Instant message contact management in a contact center
US8462935Feb 10, 2012Jun 11, 2013Intellisist, Inc.System and method for monitoring an automated voice response system
US8467519Jun 23, 2008Jun 18, 2013Intellisist, Inc.System and method for processing calls in a call center
US8499301Nov 1, 2006Jul 30, 2013Avaya Inc.Dynamically allocating server resources to competing classes of work based upon achievement of service goals
US8503663Jun 30, 2006Aug 6, 2013Interactive Intelligence, Inc.System and method for agent queue activation in a contact center
US8504534Sep 26, 2007Aug 6, 2013Avaya Inc.Database structures and administration techniques for generalized localization of database items
US8549107May 6, 2011Oct 1, 2013Oracle International CorporationSystems and methods for handling a plurality of communications for different companies
US8560369Nov 1, 2007Oct 15, 2013Red Hat, Inc.Systems and methods for technical support based on a flock structure
US8565386Sep 29, 2009Oct 22, 2013Avaya Inc.Automatic configuration of soft phones that are usable in conjunction with special-purpose endpoints
US8577015Sep 16, 2005Nov 5, 2013Avaya Inc.Method and apparatus for the automated delivery of notifications to contacts based on predicted work prioritization
US8577018 *Mar 18, 2011Nov 5, 2013Shoretel, Inc.Systems and methods for providing agent queues
US8578396May 27, 2010Nov 5, 2013Avaya Inc.Deferred control of surrogate key generation in a distributed processing architecture
US8583466Mar 21, 2006Nov 12, 2013Oracle International CorporationSystem and method for routing workflow items based on workflow templates in a call center
US8594285Jun 21, 2011Nov 26, 2013Mattersight CorporationMethod and system for analyzing separated voice data of a telephonic communication between a customer and a contact center by applying a psychological behavioral model thereto
US8621011May 12, 2009Dec 31, 2013Avaya Inc.Treatment of web feeds as work assignment in a contact center
US8644491Aug 21, 2009Feb 4, 2014Avaya Inc.Mechanism for multisite service state description
US8666040 *Sep 22, 2006Mar 4, 2014International Business Machines CorporationAnalyzing Speech Application Performance
US8670548Dec 9, 2008Mar 11, 2014Satmap International Holdings LimitedJumping callers held in queue for a call center routing system
US8675860Feb 16, 2012Mar 18, 2014Avaya Inc.Training optimizer for contact center agents
US8676625Sep 11, 2012Mar 18, 2014International Business Machines CorporationCustomer terminal for conducting a video conference between the customer terminal and an operator terminal and in which an estimated wait time is determined based on operator skill and an average dealing time
US8687795Sep 23, 2011Apr 1, 2014Eric D. KosibaSystem and method for generating forecasts and analysis of contact center behavior for planning purposes
US8688486 *Jul 13, 2007Apr 1, 2014International Business Machines CorporationSystem, method and program for setting wage for call center personnel
US8693666Jun 14, 2011Apr 8, 2014Mci Communications CorporationIntelligent call platform for an intelligent distributed network
US8699694Aug 26, 2010Apr 15, 2014Satmap International Holdings LimitedPrecalculated caller-agent pairs for a call center routing system
US8699696Sep 28, 2012Apr 15, 2014Avaya Inc.System and method for efficiently managing large contact centers
US8705723 *Jan 7, 2010Apr 22, 2014Witness Systems Inc.Systems and methods for scheduling contact center agents
US8718262Mar 30, 2007May 6, 2014Mattersight CorporationMethod and system for automatically routing a telephonic communication base on analytic attributes associated with prior telephonic communication
US8718271Aug 29, 2008May 6, 2014Satmap International Holdings LimitedCall routing methods and systems based on multiple variable standardized scoring
US8724797Aug 26, 2010May 13, 2014Satmap International Holdings LimitedEstimating agent performance in a call routing center system
US8731177Oct 1, 2008May 20, 2014Avaya Inc.Data model of participation in multi-channel and multi-party contacts
US8731178Dec 14, 2012May 20, 2014Satmap International Holdings LimitedSystems and methods for routing callers to an agent in a contact center
US8737173Feb 24, 2006May 27, 2014Avaya Inc.Date and time dimensions for contact center reporting in arbitrary international time zones
US8738732Feb 24, 2006May 27, 2014Liveperson, Inc.System and method for performing follow up based on user interactions
US8751274Jun 19, 2008Jun 10, 2014Avaya Inc.Method and apparatus for assessing the status of work waiting for service
US8762313Jun 10, 2011Jun 24, 2014Liveperson, Inc.Method and system for creating a predictive model for targeting web-page to a surfer
US8767944Jan 3, 2007Jul 1, 2014Avaya Inc.Mechanism for status and control communication over SIP using CODEC tunneling
US8781099Dec 19, 2007Jul 15, 2014At&T Intellectual Property I, L.P.Dynamic force management system
US8781100Jun 24, 2009Jul 15, 2014Satmap International Holdings LimitedProbability multiplier process for call center routing
US8781102Nov 5, 2013Jul 15, 2014Mattersight CorporationMethod and system for analyzing a communication by applying a behavioral model thereto
US8781106Aug 29, 2008Jul 15, 2014Satmap International Holdings LimitedAgent satisfaction data for call routing based on pattern matching algorithm
US20080133262 *Feb 6, 2008Jun 5, 2008International Business Machines CorporationSystem and method for calculating and displaying estimated wait times for transaction request based on the skill required to process the transaction request
US20100088145 *Jan 25, 2008Apr 8, 2010P & W Solutions Co. Ltd.Method and computer for creating communicator's schedule
US20100114644 *Jan 7, 2010May 6, 2010Jason FamaSystems and methods for scheduling contact center agents
US20100158238 *Dec 22, 2008Jun 24, 2010Oleg SaushkinSystem for Routing Interactions Using Bio-Performance Attributes of Persons as Dynamic Input
US20100274637 *Apr 23, 2009Oct 28, 2010Avaya Inc.Prediction of threshold exceptions based on real time operating information
US20120134487 *Nov 29, 2010May 31, 2012Avaya Inc.Predicted percent service level
US20120257518 *Apr 6, 2011Oct 11, 2012George ErhartReal-time probability based contact handling time
US20120263293 *Apr 15, 2011Oct 18, 2012Verizon Patent And Licensing Inc.Dynamic update of skills database
US20130013359 *Jul 8, 2011Jan 10, 2013Avaya Inc.System and method for scheduling based on service completion objectives
US20130022194 *Jul 19, 2011Jan 24, 2013Avaya Inc.Agent skill promotion and demotion based on contact center state
US20140140495 *Nov 19, 2012May 22, 2014Genesys Telecommunications Laboratories, Inc.System and method for contact center activity routing based on agent preferences
USRE43361Jan 24, 2002May 8, 2012Mci Communications CorporationTelecommunications system having separate switch intelligence and switch fabric
USRE44979Nov 5, 2012Jul 1, 2014Noble Systems CorporationSystem and method for common account based routing of contact records
WO2002103464A2 *May 15, 2002Dec 27, 2002Genesys Telecomm Lab IncMethod and apparatus for skills-based task routing
WO2004038596A1 *Aug 14, 2001Feb 14, 2002Telephony Work IncCall center administration manager with rules-based routing prioritization
Classifications
U.S. Classification379/265.12, 379/266.01, 379/309
International ClassificationH04M3/523, H04M3/42, G06F9/50
Cooperative ClassificationH04M3/5232, H04M3/5233
European ClassificationH04M3/523D2, H04M3/523D
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